A robust modeling approach for regional water management under multiple uncertainties

In regional water management systems, various uncertainties may be derived from random feature of resource conditions and natural processes, errors in estimated modeling parameters, as well as imprecision or fuzziness human-induced. This leads to difficulties in formulating and solving the resulting regional water management problems. In this study, a robust multistage interval-stochastic programming (RISP) method is developed for dealing with vague and random information in regional water management systems. The decision variables are useful for justifying and/or adjusting the decision schemes for agricultural activities through the incorporation of their implicit knowledge on regional water management. Different policies for agricultural water supply have been analyzed. The results can help to identify desired water-allocation schemes for agricultural sustainable development that the prerequisite water demand for supporting crops' survival can be guaranteed when the water resource is scarce.